WTCCC case-control study for Bipolar Disorder - Combined Controls

WTCCC genome-wide case-control association study for Bipolar Disorder (BD) using six disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

Type: Other
Archiver: European Genome-Phenome Archive (EGA)

9 Datasets 12 Publications

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID	Description	Technology	Samples
EGAD00000000001	WTCCC1 project samples from 1958 British Birth Cohort	Affymetrix 500K	1504
EGAD00000000002	WTCCC1 project samples from UK National Blood Service	Affymetrix 500K	1500
EGAD00000000003	WTCCC1 project Bipolar Disorder (BD) samples		1
EGAD00000000004	WTCCC1 project Coronary Artery Disease (CAD) samples		1
EGAD00000000005	WTCCC1 project Inflammatory Bowel Disease (IBD) samples		1
EGAD00000000006	WTCCC1 project Hypertension (HT) samples		1
EGAD00000000007	WTCCC1 project Rheumatooid arthritis (RA) samples		1
EGAD00000000008	WTCCC1 project Type 1 Diabetes (T1D) samples		1
EGAD00000000009	WTCCC1 project Type 2 Diabetes (T2D) samples		1

Publications	Citations
Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Wellcome Trust Case Control Consortium. Nature 447: 2007 661-678	5950
Targeted genomic analysis reveals widespread autoimmune disease association with regulatory variants in the TNF superfamily cytokine signalling network. Richard AC, Peters JE, Lee JC, Vahedi G, Schäffer AA, Siegel RM, Lyons PA, Smith KG. Genome Med 8: 2016 76	9
Genome-wide association study identifies distinct genetic contributions to prognosis and susceptibility in Crohn's disease. Lee JC, Biasci D, Roberts R, Gearry RB, Mansfield JC, Ahmad T, Prescott NJ, Satsangi J, Wilson DC, Jostins L, Anderson CA, UK IBD Genetics Consortium, Traherne JA, Lyons PA, Parkes M, Smith KG. Nat Genet 49: 2017 262-268	134
Leveraging functional annotations in genetic risk prediction for human complex diseases. Hu Y, Lu Q, Powles R, Yao X, Yang C, Fang F, Xu X, Zhao H. PLoS Comput Biol 13: 2017 e1005589	91
Joint modeling of genetically correlated diseases and functional annotations increases accuracy of polygenic risk prediction. Hu Y, Lu Q, Liu W, Zhang Y, Li M, Zhao H. PLoS Genet 13: 2017 e1006836	39
Leveraging putative enhancer-promoter interactions to investigate two-way epistasis in Type 2 Diabetes GWAS. Manduchi E, Chesi A, Hall MA, Grant SFA, Moore JH. Pac Symp Biocomput 23: 2018 548-558	1
Leveraging epigenomics and contactomics data to investigate SNP pairs in GWAS. Manduchi E, Williams SM, Chesi A, Johnson ME, Wells AD, Grant SFA, Moore JH. Hum Genet 137: 2018 413-425	6
SumHer better estimates the SNP heritability of complex traits from summary statistics. Speed D, Balding DJ. Nat Genet 51: 2019 277-284	100
Genomic GPS: using genetic distance from individuals to public data for genomic analysis without disclosing personal genomes. Kim K, Baik H, Jang CS, Roh JK, Eskin E, Han B. Genome Biol 20: 2019 175	3
Discovering genetic interactions bridging pathways in genome-wide association studies. Fang G, Wang W, Paunic V, Heydari H, Costanzo M, Liu X, Liu X, VanderSluis B, Oately B, Steinbach M, Van Ness B, Schadt EE, Pankratz ND, Boone C, Kumar V, Myers CL. Nat Commun 10: 2019 4274	39
shaPRS: Leveraging shared genetic effects across traits or ancestries improves accuracy of polygenic scores. Kelemen M, Vigorito E, Fachal L, Anderson CA, Wallace C. Am J Hum Genet 111: 2024 1006-1017	2
Unveiling new genetic insights in rheumatoid arthritis for drug discovery through Taxonomy3 analysis. Kozlowska J, Humphryes-Kirilov N, Pavlovets A, Connolly M, Kuncheva Z, Horner J, Manso AS, Murray C, Fox JC, McCarthy A. Sci Rep 14: 2024 14153	0